, pages 47, July 2021. European Commission: Directorate-General for Informatics, Publications Office of the European Union, ISA2 Programme\n
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@InProceedings{Alexiev-ENDORSE-2021,\n author = {Vladimir Alexiev},\n title = {{Diverse Uses of a Semantic Graph Database for Knowledge Organization and Research}},\n booktitle = {{European Data Conference on Reference Data and Semantics (ENDORSE 2021)}},\n year = 2021,\n pages = 47,\n month = jul,\n organization = {European Commission: Directorate-General for Informatics, Publications Office of the European Union, ISA2 Programme},\n url = {https://op.europa.eu/o/opportal-service/download-handler?identifier=41b06a9b-e388-11eb-895a-01aa75ed71a1&format=pdf&language=en&productionSystem=cellar},\n url_Github = {https://github.com/VladimirAlexiev/ontotext-graphdb-applications},\n url_PPT = {https://github.com/VladimirAlexiev/ontotext-graphdb-applications/raw/master/Diverse%20Uses%20of%20a%20Semantic%20Graph%20Database%20for%20Knowledge%20Organization%20and%20Research%20(ENDORSE%202021).pptx},\n url_Slides = {https://op.europa.eu/documents/7525478/8087182/ALEXIEV_presentation_Diverse+Uses+of+a+Semantic+Graph+Database+for+Knowledge+Organization+and+Research.pdf/b27afc2c-3db7-749b-c50c-52b3ded79f3c},\n url_Video = {https://www.youtube.com/watch?v=0q63x2P1V0o&list=PLT5rARDev_rmGr_LJkr7zcI-Qul7yOOHO&index=4&t=4780s},\n url_Zotero = {https://www.zotero.org/groups/2744757/ontotext-graphdb},\n keywords = {bibliography, semantic database, graph database, semantic repository, knowledge graph, Knowledge Organization System, VocBench, PoolParty, Synaptica, Semaphore, EuroVoc, AgroVoc, Getty Vocabularies, social media analytics, data marketplaces, business process management, enterprise data integration, statistical data, engineering, smart cities, sensor networks, life sciences, biomedical ontologies, medicines, chemistry, linguistic data, semantic publishing, semantic text analysis, geographic information, master data management, academic/research data, COVID, Zika virus, Quran, bilingual data, art history, Holocaust research, musical events, musical adaptations, iconography, food and drink, tourism, investment decision support, economic research, offshore leaks, maritime data, construction projects, building information management, crisis management, critical incidents, data journalism, clinical trials, investment recommendations, data journalism,},\n doi = {10.2830/44569},\n isbn = {978-92-78-42416-9},\n annote = {Catalogue number: OA-03-21-303-EN-N},\n date = {2021-07-12},\n abstract = {Semantic Graph Databases are the foundation of Enterprise Knowledge Graphs. They are used in numerous industrial applications, but also Knowledge Organization Management systems (thesaurus and ontology management systems), such as VocBench, SWC PoolParty, Synaptica Semaphore. Through VocBench, semantic databases manage or publish some of the most important thesauri: EuroVoc, AgroVoc, the Getty Vocabularies, etc. Semantic databases are also used in a wide variety of research domains and projects. Some have open source or free editions that make them an easy choice for academic research. We searched on Google Scholar and found 1000-1200 academic papers and theses mentioning one of the popular databases. We also found at least 50 books on Google Books that mention it. We started a Zotero bibliography on the topic (currently about 150 papers), and captured about 220 research topics, based on the titles of about 250 papers. We will present an analysis of reference data and research domains using a semantic database. Some of the traditional topics include: social media analytics, data marketplaces, business process management, enterprise data integration, statistical data, engineering, smart cities, sensor networks, life sciences, biomedical ontologies, medicines, chemistry, linguistic data, semantic publishing, semantic text analysis, geographic information, master data management. Newer or more exotic topics include academic/research data, COVID and Zika viruses, Quran and bilingual Arabic-English data, art history, Holocaust research, musical events and adaptations, iconography, food and drink, tourism, investment decision support, economic research, offshore leaks, maritime data, construction projects, building information management, crisis management, critical incidents and infrastructures, data journalism, clinical trials and specific medical topics (e.g. intestinal cells, intracoronal tooth restorations, vaccines, toxicology), investment recommendations, data journalism, etc.},\n}\n\n
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\n Semantic Graph Databases are the foundation of Enterprise Knowledge Graphs. They are used in numerous industrial applications, but also Knowledge Organization Management systems (thesaurus and ontology management systems), such as VocBench, SWC PoolParty, Synaptica Semaphore. Through VocBench, semantic databases manage or publish some of the most important thesauri: EuroVoc, AgroVoc, the Getty Vocabularies, etc. Semantic databases are also used in a wide variety of research domains and projects. Some have open source or free editions that make them an easy choice for academic research. We searched on Google Scholar and found 1000-1200 academic papers and theses mentioning one of the popular databases. We also found at least 50 books on Google Books that mention it. We started a Zotero bibliography on the topic (currently about 150 papers), and captured about 220 research topics, based on the titles of about 250 papers. We will present an analysis of reference data and research domains using a semantic database. Some of the traditional topics include: social media analytics, data marketplaces, business process management, enterprise data integration, statistical data, engineering, smart cities, sensor networks, life sciences, biomedical ontologies, medicines, chemistry, linguistic data, semantic publishing, semantic text analysis, geographic information, master data management. Newer or more exotic topics include academic/research data, COVID and Zika viruses, Quran and bilingual Arabic-English data, art history, Holocaust research, musical events and adaptations, iconography, food and drink, tourism, investment decision support, economic research, offshore leaks, maritime data, construction projects, building information management, crisis management, critical incidents and infrastructures, data journalism, clinical trials and specific medical topics (e.g. intestinal cells, intracoronal tooth restorations, vaccines, toxicology), investment recommendations, data journalism, etc.\n